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I recently joined NVIDIA as a Distinguished Engineer, where I’m developing VLSI AI Agents that leverage large language models (LLMs) to accelerate hardware design.
My research interests include deep learning and information theory, Google Scholar.
Past work experiences
- I was a ML researcher at Google Research (see selected research projects below)

Developing General AI Agents with Gemini Multimodality
- Leveraged Langfun and Gemini’s multimodal capabilities to build a general-purpose AI agent, achieving SOTA performance on the GAIA benchmark in December 2024. This project demonstrated the effectiveness of Langfun + Gemini for complex reasoning and task completion across diverse domains.
- Adapted the general-purpose AI agent idea to create a specialized vision-only AI agent for automated proofreading of large-scale 3D neuron reconstructions in mouse brain microscopy datasets on neuroglancer.
Applying Deep Learning to Drug Discovery
- Our publication in the Journal of Medicinal Chemistry, for the first time, discovered a novel small molecule ligand for WDR91 by using affinity-mediated DNA-encoded chemical library selection followed by deep learning. WDR’s unique β-propeller structure makes them attractive targets, but most human WDRs are unexplored compared to other major drug target families. The discovery of a drug-like small molecule and its covalent analog compounds will soon enable researchers to identify a WDR91 drug candidate.
- Talk
Studying secure communication from information theoretic perspective
- Our publication in IEEE Transactions on Information Theory provided new insights into secure communication over broadcast channels by developing both inner and outer bounds for the rate equivocation region.
- Ph.D. Dissertation

Ph.D. in Electrical and Computer Engineering, Syracuse University, 2009
M.S. in Computer Science, Chinese Academy of Science, Institute of Automation, 2005
B.S. in Electronic Engineering and Information Science, University of Science and Technology of China, 2002